ArticleBMC bioinformatics2015
Cell-composition effects in the analysis of DNA methylation array data: a mathematical perspective.
Article in BMC bioinformatics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 66 papers, 2 of them syntheses that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
66 citing papers in PubMed, 2 syntheses or guidelines pooled it, 132 citations in OpenAlex.
- Systematic review on the DNA methylation role in endometriosis: current evidence and perspectives.Clinical epigenetics · 2025Pooled it
- A DNA methylation biomarker of alcohol consumption.Molecular psychiatry · 2018Pooled it
- Causal relationship between epigenetic markers and type 2 diabetes in West African populations: a Mendelian randomisation analysis.Diabetologia · 2026Article
- DNA methylation heterogeneity in complex tumor microenvironment: Quantitative methods, influencing factors, and clinical implications.Genes & diseases · 2026Review
- Early life trauma patterns and adult epigenome-wide and NR3C1-specific DNA methylation in the Sister Study.American journal of epidemiology · 2026Article
- Examining the timing of trauma, PTSD onset, and DNA methylation: A multicohort investigation of candidate CpG sites.Journal of psychiatric research · 2025Article
- Association of Epigenetic Markers of Aging With Prevalent and Incident Type 2 Diabetes.The journals of gerontology. Series A, Biological sciences and medical sciences · 2025Article
- Pubertal timing as a predictor of epigenetic aging and mortality risk in young adulthood.Developmental psychology · 2025Article
- Epigenome-Wide and Methylation Risk Score Analysis of Body Mass Index Among People with HIV.Epigenomes · 2024Article
- Epigenetic aging of semen is associated with inflammation.Epigenetics · 2024Article
- Placental and immune cell DNA methylation reference panel for bulk tissue cell composition estimation in epidemiological studies.Epigenetics · 2024Article
- A multi-trait epigenome-wide association study identified DNA methylation signature of inflammation among men with HIV.Clinical epigenetics · 2024Article
- Serotonin Transporter (SLC6A4) and FK506-Binding Protein 5 (FKBP5) Genotype and Methylation Relationships with Response to Meditation in Veterans with PTSD.Molecular neurobiology · 2024Article
- Article
- A multi-trait epigenome-wide association study identified DNA methylation signature of inflammation among people with HIV.Research square · 2024Article
- Investigating neonatal health risk variables through cell-type specific methylome-wide association studies.Clinical epigenetics · 2024Article
- Epigenetic aging in older people living with HIV in Eswatini: a pilot study of HIV and lifestyle factors and epigenetic aging.Clinical epigenetics · 2024Article
- Genomic hypomethylation in cell-free DNA predicts responses to checkpoint blockade in lung and breast cancer.Scientific reports · 2023Article
- Article
- Circulating triglycerides are associated with human adipose tissue DNA methylation of genes linked to metabolic disease.Human molecular genetics · 2023Article
6 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 3 institutions in 1 country.
Funding
Abstract
backgroundThe impact of cell-composition effects in analysis of DNA methylation data is now widely appreciated. With the availability of a reference data set consisting of DNA methylation measurements on isolated cell types, it is possible to impute cell proportions and adjust for them, but there is increasing interest in methods that adjust for cell composition effects when reference sets are incomplete or unavailable.
resultsIn this article we present a theoretical basis for one such method, showing that the total effect of a phenotype on DNA methylation can be decomposed into orthogonal components, one representing the effect of phenotype on proportions of major cell types, the other representing either subtle effects in composition or global effects at focused loci, and that it is possible to separate these two types of effects in a finite data set. We demonstrate this principle empirically on nine DNA methylation data sets, showing that the first few principal components generally contain a majority of the information on cell-type present in the data, but that later principal components nevertheless contain information about a small number of loci that may represent more focused associations. We also present a new method for determining the number of linear terms to interpret as cell-mixture effects and demonstrate robustness to the choice of this parameter.
conclusionsTaken together, our work demonstrates that reference-free algorithms for cell-mixture adjustment can produce biologically valid results, separating cell-mediated epigenetic effects (i.e. apparent effects arising from differences in cell composition) from those that are not cell mediated, and that in general the interpretation of associations evident from DNA methylation should be carefully considered.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.